Changeset 21759 for issm/branches/trunk-larour-NatGeoScience2016/src/py3/interp/averaging.py

Timestamp:

06/07/17 10:50:54 (8 years ago)

Author:

Eric.Larour

Message:

CHG: merged branch back to trunk-jpl 21754.

File:

• issm/branches/trunk-larour-NatGeoScience2016/src/py3/interp/averaging.py (modified) (4 diffs)

issm/branches/trunk-larour-NatGeoScience2016/src/py3/interp/averaging.py

@@ -1 @@
-import numpy as npy
+import numpy as np
 from GetAreas import GetAreas
 from scipy.sparse import csc_matrix
@@ -36 +36 @@
         #initialization
         if layer==0:
-                weights=npy.zeros(md.mesh.numberofvertices,)
+                weights=np.zeros(md.mesh.numberofvertices,)
                 data=data.flatten(1)
         else:
-                weights=npy.zeros(md.mesh.numberofvertices2d,)
+                weights=np.zeros(md.mesh.numberofvertices2d,)
                 data=data[(layer-1)*md.mesh.numberofvertices2d+1:layer*md.mesh.numberofvertices2d,:]
         
@@ -66 +66 @@
         index=index-1 # since python indexes starting from zero
         line=index.flatten(1)
-        areas=npy.vstack(areas).reshape(-1,)
-        summation=1./rep*npy.ones(rep,)
+        areas=np.vstack(areas).reshape(-1,)
+        summation=1./rep*np.ones(rep,)
         linesize=rep*numberofelements
         
         #update weights that holds the volume of all the element holding the node i
-        weights=csc_matrix( (npy.tile(areas,(rep,1)).reshape(-1,),(line,npy.zeros(linesize,))), shape=(numberofnodes,1))
+        weights=csc_matrix( (np.tile(areas,(rep,1)).reshape(-1,),(line,np.zeros(linesize,))), shape=(numberofnodes,1))
         
         #initialization
         if len(data)==numberofelements:
-                average_node=csc_matrix( (npy.tile(areas*data,(rep,1)).reshape(-1,),(line,npy.zeros(linesize,))), shape=(numberofnodes,1))
+                average_node=csc_matrix( (np.tile(areas*data,(rep,1)).reshape(-1,),(line,np.zeros(linesize,))), shape=(numberofnodes,1))
                 average_node=average_node/weights
                 average_node = csc_matrix(average_node)
@@ -82 +82 @@
 
         #loop over iteration
-        for i in npy.arange(1,iterations+1):
-                average_el=npy.asarray(npy.dot(average_node.todense()[index].reshape(numberofelements,rep),npy.vstack(summation))).reshape(-1,)
-                average_node=csc_matrix( (npy.tile(areas*average_el.reshape(-1),(rep,1)).reshape(-1,),(line,npy.zeros(linesize,))), shape=(numberofnodes,1))
+        for i in np.arange(1,iterations+1):
+                average_el=np.asarray(np.dot(average_node.todense()[index].reshape(numberofelements,rep),np.vstack(summation))).reshape(-1,)
+                average_node=csc_matrix( (np.tile(areas*average_el.reshape(-1),(rep,1)).reshape(-1,),(line,np.zeros(linesize,))), shape=(numberofnodes,1))
                 average_node=average_node/weights
                 average_node=csc_matrix(average_node)
         
         #return output as a full matrix (C code do not like sparse matrices)
-        average=npy.asarray(average_node.todense()).reshape(-1,)
+        average=np.asarray(average_node.todense()).reshape(-1,)
 
         return average